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de Zambotti M, Goldstein C, Cook J, Menghini L, Altini M, Cheng P, Robillard R. State of the science and recommendations for using wearable technology in sleep and circadian research. Sleep 2024; 47:zsad325. [PMID: 38149978 DOI: 10.1093/sleep/zsad325] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 12/21/2023] [Indexed: 12/28/2023] Open
Abstract
Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research.
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Affiliation(s)
- Massimiliano de Zambotti
- Center for Health Sciences, SRI International, Menlo Park, CA, USA
- Lisa Health Inc., Oakland, CA, USA
| | - Cathy Goldstein
- Sleep Disorders Center, Department of Neurology, University of Michigan-Ann Arbor, Ann Arbor, MI, USA
| | - Jesse Cook
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Luca Menghini
- Department of Psychology and Cognitive Science, University of Trento, Trento, Italy
| | - Marco Altini
- Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip Cheng
- Sleep Disorders and Research Center, Henry Ford Health, Detroit, MI, USA
| | - Rebecca Robillard
- School of Psychology, University of Ottawa, Ottawa, ON, Canada
- Canadian Sleep Research Consortium, Canada
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Bloomfield LSP, Fudolig MI, Kim J, Llorin J, Lovato JL, McGinnis EW, McGinnis RS, Price M, Ricketts TH, Dodds PS, Stanton K, Danforth CM. Predicting stress in first-year college students using sleep data from wearable devices. PLOS DIGITAL HEALTH 2024; 3:e0000473. [PMID: 38602898 PMCID: PMC11008774 DOI: 10.1371/journal.pdig.0000473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 02/16/2024] [Indexed: 04/13/2024]
Abstract
Consumer wearables have been successful at measuring sleep and may be useful in predicting changes in mental health measures such as stress. A key challenge remains in quantifying the relationship between sleep measures associated with physiologic stress and a user's experience of stress. Students from a public university enrolled in the Lived Experiences Measured Using Rings Study (LEMURS) provided continuous biometric data and answered weekly surveys during their first semester of college between October-December 2022. We analyzed weekly associations between estimated sleep measures and perceived stress for participants (N = 525). Through mixed-effects regression models, we identified consistent associations between perceived stress scores and average nightly total sleep time (TST), resting heart rate (RHR), heart rate variability (HRV), and respiratory rate (ARR). These effects persisted after controlling for gender and week of the semester. Specifically, for every additional hour of TST, the odds of experiencing moderate-to-high stress decreased by 0.617 or by 38.3% (p<0.01). For each 1 beat per minute increase in RHR, the odds of experiencing moderate-to-high stress increased by 1.036 or by 3.6% (p<0.01). For each 1 millisecond increase in HRV, the odds of experiencing moderate-to-high stress decreased by 0.988 or by 1.2% (p<0.05). For each additional breath per minute increase in ARR, the odds of experiencing moderate-to-high stress increased by 1.230 or by 23.0% (p<0.01). Consistent with previous research, participants who did not identify as male (i.e., female, nonbinary, and transgender participants) had significantly higher self-reported stress throughout the study. The week of the semester was also a significant predictor of stress. Sleep data from wearable devices may help us understand and to better predict stress, a strong signal of the ongoing mental health epidemic among college students.
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Affiliation(s)
- Laura S. P. Bloomfield
- Gund Institute for Environment, University of Vermont, Burlington, Vermont, United States of America
- Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont, United States of America
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
| | - Mikaela I. Fudolig
- Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont, United States of America
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
| | - Julia Kim
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
| | - Jordan Llorin
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
| | - Juniper L. Lovato
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
| | - Ellen W. McGinnis
- Department of Social Science and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Remote Patient and Participant Monitoring, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Ryan S. McGinnis
- Center for Remote Patient and Participant Monitoring, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Matt Price
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
- Department of Psychological Science, University of Vermont, Burlington, Vermont, United States of America
| | - Taylor H. Ricketts
- Gund Institute for Environment, University of Vermont, Burlington, Vermont, United States of America
- Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, Vermont, United States of America
| | - Peter Sheridan Dodds
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
- Department of Computer Science, University of Vermont, Burlington, Vermont, United States of America
| | - Kathryn Stanton
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
| | - Christopher M. Danforth
- Gund Institute for Environment, University of Vermont, Burlington, Vermont, United States of America
- Department of Mathematics & Statistics, University of Vermont, Burlington, Vermont, United States of America
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
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Menghini L, Balducci C, de Zambotti M. Is it Time to Include Wearable Sleep Trackers in the Applied Psychologists' Toolbox? THE SPANISH JOURNAL OF PSYCHOLOGY 2024; 27:e8. [PMID: 38410074 DOI: 10.1017/sjp.2024.8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Wearable sleep trackers are increasingly used in applied psychology. Particularly, the recent boom in the fitness tracking industry has resulted in a number of relatively inexpensive consumer-oriented devices that further enlarge the potential applications of ambulatory sleep monitoring. While being largely positioned as wellness tools, wearable sleep trackers could be considered useful health devices supported by a growing number of independent peer-reviewed studies evaluating their accuracy. The inclusion of sensors that monitor cardiorespiratory physiology, diurnal activity data, and other environmental signals allows for a comprehensive and multidimensional approach to sleep health and its impact on psychological well-being. Moreover, the increasingly common combination of wearable trackers and experience sampling methods has the potential to uncover within-individual processes linking sleep to daily experiences, behaviors, and other psychosocial factors. Here, we provide a concise overview of the state-of-the-art, challenges, and opportunities of using wearable sleep-tracking technology in applied psychology. Specifically, we review key device profiles, capabilities, and limitations. By providing representative examples, we highlight how scholars and practitioners can fully exploit the potential of wearable sleep trackers while being aware of the most critical pitfalls characterizing these devices. Overall, consumer wearable sleep trackers are increasingly recognized as a valuable method to investigate, assess, and improve sleep health. Incorporating such devices in research and professional practice might significantly improve the quantity and quality of the collected information while opening the possibility of involving large samples over representative time periods. However, a rigorous and informed approach to their use is necessary.
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Affiliation(s)
- Luca Menghini
- Università di Trento (Italy)
- Università degli Studi di Padova (Italy)
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Ng ASC, Massar SAA, Bei B, Chee MWL. Assessing 'readiness' by tracking fluctuations in daily sleep duration and their effects on daily mood, motivation, and sleepiness. Sleep Med 2023; 112:30-38. [PMID: 37804715 DOI: 10.1016/j.sleep.2023.09.028] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/19/2023] [Accepted: 09/25/2023] [Indexed: 10/09/2023]
Abstract
STUDY OBJECTIVES Consumer sleep trackers issue daily guidance on 'readiness' without clear empirical basis. We investigated how self-rated mood, motivation, and sleepiness (MMS) levels are affected by daily fluctuations in sleep duration, timing, and efficiency and overall sleep regularity. We also determined how temporally specific these associations are. METHODS 119 healthy university students (64 female, mean age = 22.54 ± 1.74 years) wore a wearable sleep tracker and undertook twice-daily smartphone-delivered ecological momentary assessment of mood, motivation, and sleepiness at post-wake and pre-bedtime timings for 2-6 weeks. Naps and their duration were reported daily. Nocturnal sleep on 2471 nights were examined using multilevel models to uncover within-subject and between-subject associations between sleep duration, timing, efficiency, and nap duration on following day MMS ratings. Time-lagged analyses examined the temporal specificity of these associations. Linear regression models investigated associations between MMS ratings and sleep variability, controlling for sleep duration. RESULTS Nocturnal sleep durations were short (6.03 ± 0.71 h), and bedtimes were late (1:42AM ± 1:05). Within-subjects, nocturnal sleep longer than a person's average was associated with better mood, higher motivation, and lower sleepiness after waking. Effects of such longer sleep duration lingered for mood and sleepiness till the pre-bedtime window (all Ps < .005) but did not extend to the next day. Between-subjects, higher intraindividual sleep variability, but not sleep duration, was associated with poorer mood and lower motivation after waking. Longer average sleep duration was associated with less sleepiness after waking and lower motivation pre-bedtime (all Ps < .05). Longer naps reduced post-nap sleepiness and improved mood. Controlling for nocturnal sleep duration, longer naps also associated with lower post-waking sleepiness on the following day. CONCLUSIONS Positive connections between nocturnal sleep and nap duration with MMS are temporally circumscribed, lending credence to the construction of sleep-based, daily 'readiness' scores. Higher sleep duration variability lowers an individual's post waking mood and motivation. CLINICAL TRIAL ID ClinicalTrials.gov NCT04880629.
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Affiliation(s)
- Alyssa S C Ng
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Stijn A A Massar
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Bei Bei
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Michael W L Chee
- Sleep and Cognition Laboratory, Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
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Gao T, Tao Y, Wang Q, Liu J, Du Z, Xing Y, Chen F, Mei J. A bibliometric analysis of insomnia in adolescent. Front Psychiatry 2023; 14:1246808. [PMID: 37965363 PMCID: PMC10641400 DOI: 10.3389/fpsyt.2023.1246808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 10/10/2023] [Indexed: 11/16/2023] Open
Abstract
Background The negative effects of insomnia on adolescents' development, academic performance, and quality of life place a burden on families, schools, and society. As one of the most important research directions for insomnia, adolescent insomnia has significant research value, social value, and practical significance. Unfortunately, there is no bibliometric analysis in this field of study. This study aims to analyze published articles using bibliometrics, summarize the current research progress and hot topics in this field systematically and exhaustively, and predict the future direction and trend of research. Methods For this study, the Web of Science Core Collection (WoSCC) database was searched between 2002 and 2022 for publications related to adolescent insomnia. The R-bibliometrix, VOSViewer, and CiteSpace software were utilized for bibliometric analysis. Results This investigation included 2468 publications from 3102 institutions in 87 countries, led by China and the United States. This field of research has entered a period of rapid development since 2017. The journal with the most publications on adolescent insomnia is Sleep, which is also the most co-cited journal. American Journal of Psychology has the highest impact factor among the top 10 journals. These papers were written by 10605 authors; notably, Liu Xianchen emerged as the author with the highest frequency of publications, while Mary A. Carskadon was the most frequently co-cited author. Mental health and comorbid diseases were the main research directions in this field. "Depression," "anxiety," "mental health," "COVID-19," "stress," "quality of life," "heart rate variability," and "attention-deficit hyperactivity disorder" were hot spots and trends in this field at the current moment. Conclusion The research on adolescent insomnia has social value, research value, and research potential; its development is accelerating, and an increasing number of researchers are focusing on it. This study summarized and analyzed the development process, hot spots, and trends of adolescent insomnia research using bibliometric analysis, which identified the current hot topics in this field and predicted the development trend for the future.
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Affiliation(s)
- Tianci Gao
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
- First Affiliated Hospital, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Yulei Tao
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
- First Affiliated Hospital, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Qianfei Wang
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
- First Affiliated Hospital, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Jiayi Liu
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Zekun Du
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - YueYi Xing
- School of Basic Medicine, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Fenqiao Chen
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
- First Affiliated Hospital, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
| | - Jianqiang Mei
- Graduate School, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
- First Affiliated Hospital, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, China
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Zhai H, Yan Y, He S, Zhao P, Zhang B. Evaluation of the Accuracy of Contactless Consumer Sleep-Tracking Devices Application in Human Experiment: A Systematic Review and Meta-Analysis. SENSORS (BASEL, SWITZERLAND) 2023; 23:4842. [PMID: 37430756 DOI: 10.3390/s23104842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 05/12/2023] [Accepted: 05/15/2023] [Indexed: 07/12/2023]
Abstract
Compared with the gold standard, polysomnography (PSG), and silver standard, actigraphy, contactless consumer sleep-tracking devices (CCSTDs) are more advantageous for implementing large-sample and long-period experiments in the field and out of the laboratory due to their low price, convenience, and unobtrusiveness. This review aimed to examine the effectiveness of CCSTDs application in human experiments. A systematic review and meta-analysis (PRISMA) of their performance in monitoring sleep parameters were conducted (PROSPERO: CRD42022342378). PubMed, EMBASE, Cochrane CENTRALE, and Web of Science were searched, and 26 articles were qualified for systematic review, of which 22 provided quantitative data for meta-analysis. The findings show that CCSTDs had a better accuracy in the experimental group of healthy participants who wore mattress-based devices with piezoelectric sensors. CCSTDs' performance in distinguishing waking from sleeping epochs is as good as that of actigraphy. Moreover, CCSTDs provide data on sleep stages that are not available when actigraphy is used. Therefore, CCSTDs could be an effective alternative tool to PSG and actigraphy in human experiments.
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Affiliation(s)
- Huifang Zhai
- Faculty of Architecture and Urban Planning, Chongqing University, Chongqing 400044, China
- Key Laboratory of New Technology for Construction of Cities in Mountain Area, Chongqing University, Chongqing 400044, China
| | - Yonghong Yan
- Faculty of Architecture and Urban Planning, Chongqing University, Chongqing 400044, China
- Key Laboratory of New Technology for Construction of Cities in Mountain Area, Chongqing University, Chongqing 400044, China
| | - Siqi He
- College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
| | - Pinyong Zhao
- College of Mathematics and Statistics, Chongqing University, Chongqing 400044, China
| | - Bohan Zhang
- Faculty of Engineering, The University of Sydney, Camperdown, NSW 2006, Australia
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